Concurrent training (CT) is defined as the development of both endurance and strength within the same exercise program. CT has been studied for decades, but the results has been diverse. However, very few have studied the effects of CT on the upper body musculature. Hence, this review set out to investigate the effects of combined strength and endurance training (ET) of the upper body on muscle hypertrophy, muscle strength and endurance variables. PubMed was searched with relevant search terms with varying combinations, such as concurrent training, combined strength and endurance training. After scanning the literature, a total of eight articles were included. The results suggest that muscle strength, exercise economy and time to exhaustion can effectively be improved by CT of the upper body. The effect of CT on upper body musculature were unclear. Some of the articles included suggests a decrease in whole body lean mass, which might simply be due to insufficient loading of the lower body musculature. In order to maintain muscle mass during a CT protocol, endurance athletes should aim to perform ST which targets muscles active during ET. However, the limited empiric literature available on CT of the upper body makes a conclusion hard to draw. This review shows that CT of the upper body is yet an unexplored and researchers should further investigate the effects of CT for the musculature of the upper body alone. If we gain more knowledge of the effects from concurrent training of the upper body, it could have several implications, both clinically and in a sport setting.

This thesis presents a simple method for the concurrent manipulation of linearly ordered data structures on hypercubes. The method is based on the existence of a pruned binomial search tree rooted at any arbitrary node of the binary hypercube. The tree spans any arbitrary sequence of n consecutive nodes containing the root, using a fan-out of at most [log₂ 𝑛] and a depth of [log₂ 𝑛] +1. Search trees spanning non-overlapping processor lists are formed using only local information, and can be used concurrently without contention problems. Thus, they can be used for performing broadcast and merge operations simultaneously on sets with non-uniform sizes. Extensions to generalized and faulty hypercubes and applications to image processing algorithms and for m-way search are discussed.

The current study aimed to examine subgroups with different levels of attentiondeficit/hyperactivity disorder-symptoms and anxiety symptoms and how these differedregarding involvement in delinquent behavior, aggression and commitment of violent acts.We hypothesized that four subgroups would be identified, and the subgroup with high levelsof both ADHD and anxiety symptoms would report equal levels on total delinquency asadolescents with ADHD only and that it would be mostly common among adolescent boyswith ADHD to have concurrent anxiety symptoms. We also hypothesized that symptoms ofhyperactivity/impulsivity would be more related to the predicted outcomes than symptoms ofinattention. The study was conducted through self-reports of 1072 adolescent boys and girlsfrom a community-based sample in Sweden. The results of the k-mean cluster analysisrevealed four different subgroups with different levels of ADHD and anxiety symptoms,labeled ADHD-anxiety, ADHD-only, anxiety-only and non-symptom. Further, one-wayAnalysis of Variance (ANOVA) revealed that the ADHD-only subgroup reportedsignificantly higher on total delinquency and aggression than the other subgroups. ADHDanxietysubgroup reported significantly higher on minor property offenses and commitment ofviolent acts. 2x4 Factorial ANOVA revealed that anxiety were more common amongadolescent boys. Thus, inattention was found to be more strongly related to the predictedoutcomes than symptoms of hyperactivity/impulsivity. These findings suggest thatadolescents with concurrent ADHD and anxiety might need different intervention andtreatment approaches.

Modern supercomputers now use accelerators to achieve their performance with the most widely used accelerator being the Graphics Processing Unit (GPU). However, achieving the performance potential of systems that combine a GPU and CPU is an arduous task which could be made easier with the assistance of the compiler or runtime. In particular, exploiting two features of GPU architectures -- distributed memory and concurrent kernel execution -- is critical to achieve good performance, but in current GPU programming systems, programmers must exploit them manually. This can lead to poor performance. In this thesis, we propose automatic techniques that: i) perform data transfers between the CPU and GPU, ii) allocate resources for concurrent kernels, and iii) schedule concurrent kernels efficiently without programmer intervention. <p>Most GPU programs access data in GPU memory for performance. Manually inserting data transfers that move data to and from this GPU memory is an error-prone and tedious task. In this work, we develop a software coherence mechanism to fully automate all data transfers between the CPU and GPU without any assistance from the programmer. Our mechanism uses compiler analysis to identify potential stale data accesses and uses a runtime to initiate transfers as necessary. This avoids redundant transfers that are exhibited by all other existing automatic memory management proposals for general purpose programs. We integrate our automatic memory manager into the X10 compiler and runtime, and find that it not only results in smaller and simpler programs, but also eliminates redundant memory transfers. Tested on eight programs ported from the Rodinia benchmark suite it achieves (i) a 1.06x speedup over hand-tuned manual memory management, and (ii) a 1.29x speedup over another recently proposed compiler--runtime automatic memory management system. Compared to other existing runtime-only (ADSM) and compiler-only (OpenMPC) proposals, it also transfers 2.2x to 13.3x less data on average. <p>Each new generation of GPUs vastly increases the resources available to GPGPU programs. GPU programming models (like CUDA) were designed to scale to use these resources. However, we find that CUDA programs actually do not scale to utilize all available resources, with over 30% of resources going unused on average for programs of the Parboil2 suite. Current GPUs therefore allow concurrent execution of kernels to improve utilization. We study concurrent execution of GPU kernels using multiprogrammed workloads on current NVIDIA Fermi GPUs. On two-program workloads from Parboil2 we find concurrent execution is often no better than serialized execution. We identify lack of control over resource allocation to kernels as a major serialization bottleneck. We propose transformations that convert CUDA kernels into elastic kernels which permit fine-grained control over their resource usage. We then propose several elastic-kernel aware runtime concurrency policies that offer significantly better performance and concurrency than the current CUDA policy. We evaluate our proposals on real hardware using multiprogrammed workloads constructed from benchmarks in the Parboil2 suite. On average, our proposals increase system throughput (STP) by 1.21x and improve the average normalized turnaround time (ANTT) by 3.73x for two-program workloads over the current CUDA concurrency implementation. <p>Recent NVIDIA GPUs use a FIFO policy in their thread block scheduler (TBS) to schedule thread blocks of concurrent kernels. We show that FIFO leaves performance to chance, resulting in significant loss of performance and fairness. To improve performance and fairness, we propose use of the Shortest Remaining Time First (SRTF) policy instead. Since SRTF requires an estimate of runtime (i.e. execution time), we introduce Structural Runtime Prediction that uses the grid structure of GPU programs for predicting runtimes. Using a novel Staircase model of GPU kernel execution, we show that kernel runtime can be predicted by profiling only the first few thread blocks. We evaluate an online predictor based on this model on benchmarks from ERCBench and find that predictions made after the execution of single thread block are between 0.48x to 1.08x of actual runtime. %Next, we design a thread block scheduler that is both concurrent kernel-aware and incorporates this predictor. We implement the SRTF policy for concurrent kernels that uses this predictor and evaluate it on two-program workloads from ERCBench. SRTF improves STP by 1.18x and ANTT by 2.25x over FIFO. Compared to MPMax, a state-of-the-art resource allocation policy for concurrent kernels, SRTF improves STP by 1.16x and ANTT by 1.3x. To improve fairness, we also propose SRTF/Adaptive which controls resource usage of concurrently executing kernels to maximize fairness. SRTF/Adaptive improves STP by 1.12x, ANTT by 2.23x and Fairness by 2.95x compared to FIFO. Overall, our implementation of SRTF achieves STP to within 12.64% of Shortest Job First (SJF, an oracle optimal scheduling policy), bridging 49% of the gap between FIFO and SJF.

The present study contributes an apparatus and research paradigm useful in generating human performances sensitive to concurrent schedules of reinforcement. Five participants produced performances observed to be under temporal and ratio control of concurrent fixed interval-fixed ratio schedules. Two aspects of interaction between FI and FR schedules were distinguishable in the data. First, interaction between two schedules was observed in that changes in the value of one schedule affected behavior reinforced on another schedule. Second, switching from one pattern to the other functioned as an operant unit, showing stability during schedule maintenance conditions and sensitivity to extinction. These effects are discussed in the context of current views on behavior under concurrent schedules of reinforcement, and some implications for the conceptualization, measurement, analysis, and treatment of complex behavior are presented.

A programação concorrente é cada vez mais utilizada nos sistemas atuais com o objetivo de reduzir custos e obter maior eficiência no processamento. Com a importância da programação concorrente é imprescindível que programas que implementam esse paradigma apresentem boa qualidade e estejam livres de defeitos. Assim,diferentes técnicas e critérios de teste vêm sendo definidos para apoiar a validação de aplicações desenvolvidas nesse paradigma. Nesse contexto, a geração automática de dados de teste é importante, pois permite reduzir o custo na geração e seleção de dados relevantes. O uso de técnicas meta-heurísticas tem sido uma área de grande interesse entre os pesquisadores para geração de dados, pois essas técnicas apresentam abordagens aplicáveis a problemas complexos e de difícil solução. Considerando esse aspecto, este trabalho apresenta uma abordagem de geração automática de dados para o teste estrutural de programas concorrentes em MPI (Message Passing Interface). A meta-heurística usada foi Algoritmo Genético em que a busca é guiada por critérios de teste que consideram características implícitas de programas concorrentes. O desempenho da abordagem foi avaliado por meio da cobertura dos dados detestes, da eficácia em revelar defeitos e do custo de execução. Para comparação, a geração aleatória foi considerada. Os resultados indicaram que é promissor usar geração de dados de teste no contexto de programas concorrentes, com resultados interessantes em relação à eficácia e cobertura dos requisitos de teste. / Concurrent programming has been increasingly used in current systems in order to reduce costs and obtain higher processing efficiency and, consequently, it is expected that these systems have high quallity. Therefore, different techniques and testing criteria have been proposed aiming to support the verification and validation of the concurrent applications. In this context, the automated data test generation allows to reduce the testing costs during the generation and selection of data tests. Metaheuristic technique has been widely investigated to support the data test generation because this technique has presented good results to complex and costly problems. In this work, we present an approach to the automated data test generation for message passing concurrent programs in MPI (Message Passing Interface). The generation of data test is performed using the genetic algorithm metaheuristic technique, guiding by structural testing criteria. An experimental study was conducted to evaluate the proposed approach, analyzing the effectiveness and application cost. The results indicate that the genetic algorithm is a promising approach to automated test data generation for concurrent programs, presenting good results in relation to effectiveness and data test coverage.

O treinamento concorrente (TC) é frequentemente utilizado por praticantes de atividades físicas e atletas com o intuito de desenvolver a força muscular e o condicionamento aeróbio. No entanto, essa estratégia de treinamento pode atenuar os ganhos de força e hipertrofia muscular em longo prazo, efeito este conhecido como fenômeno da interferência. Há indícios na literatura de que a magnitude da interferência pode ser dependente do volume em que o exercício aeróbio é realizado. Assim, o objetivo do presente estudo foi verificar o efeito do exercício aeróbio realizado com diferentes volumes no desempenho agudo de força máxima e de resistência de força dos membros inferiores. Homens fisicamente ativos (n=21) foram submetidos a seis condições experimentais realizadas em ordem aleatória, sendo três sessões de exercício aeróbio com volumes distintos (3km, 5km e 7km) seguidas pelo teste de força dinâmica máxima (1RM) e outras três sessões de exercício aeróbio com os volumes distintos seguidas pelo teste de resistência de força (4 séries de repetições máximas a 80% 1RM). Para o exercício aeróbio foi realizada a corrida contínua em esteira rolante a 90% do limiar anaeróbio (Lan) e os testes de força foram realizados no exercício leg press 45o. Para a comparação dos valores de 1RM, volume total (VT) e número de repetições máximas (NRM) da sessão de treinamento de força (TF) foi realizada uma análise de modelo misto tendo os volumes do exercício aeróbio como fator fixo e sujeitos como fator aleatório. Testes post-hoc com ajustamento de Tukey foram utilizados para comparações múltiplas. O nível de significância adotado foi de 5%. Não foram observadas diferenças nos valores de 1RM entre as condições. O VT e NRM das condições de 5km e 7km foram menores quando comparados com a condição controle. Ao passo que, o VT da condição de 7km foi menor em relação ao VT das condições de 3km e 5km; e o NRM da condição de 7km foi menor em relação ao NRM da condição de 3km. Não foram observadas diferenças no VT e NRM entre as condições de 3km e controle e entre as condições de 3km e 5km. Em conclusão, o desempenho da resistência de força foi prejudicado após a realização do exercício aeróbio e a ocorrência e a magnitude desta interferência dependeram do volume em que o exercício aeróbio foi realizado. Adicionalmente, o desempenho da força dinâmica máxima não foi prejudicado pela realização prévia do exercício aeróbio / Concurrent training (CT) is frequently utilized by physically active individuals and athletes in order to develop muscle strength and aerobic fitness. However, this training strategy may result in attenuation of the gains on strength and muscle hypertrophy in long term. This effect has been referred to as the interference phenomenon. There are indications that the magnitude of this interference may be dependent on the volume that aerobic exercise is performed. Thus, the aim of the present study was to verify the effect of aerobic exercise performed with different volumes on the acute performance of lower limbs maximum strength and strength endurance. Physically active men (n=21) were submitted to six experimental conditions performed in random order, three aerobic exercise sessions with different volumes (3km, 5km and 7km) followed by the maximum dynamic strength (1RM) test and three aerobic exercise sessions with different volumes followed by strength endurance test (4 sets of maximum repetitions at 80% 1RM). The aerobic exercise was a continuous treadmill run at 90% of the anaerobic threshold (AT) and all strength tests were performed in the leg press 45o. A mixed-model analysis with the volumes of aerobic exercise as a fixed factor and subject as a random factor was performed to compare 1RM values, total volume (TV) and maximum number of repetitions (MNR) of the strength training (ST) session. Post-hoc tests with Tukey adjustments were used for multiple comparisons. The significance level adopted was 5%. No differences were observed in 1RM values among conditions. The TV and MNR of the 5km and 7km conditions were lower when compared to the control condition. The TV of the 7km condition was lower than the 3km and 5km conditions; and the MNR of the 7km condition was lower than the 3km condition. No differences were observed in TV and MNR between the 3km and control conditions and between the 3km and 5km conditions. In conclusion, strength endurance performance was impaired when performed after aerobic exercise and the magnitude of this interference depended on the volume of the aerobic exercise. In addition, maximum dynamic strength performance was not affected by prior execution of aerobic exercise

The purpose of this review is twofold: to elucidate the utility of resistance training for endurance athletes, and provide the practitioner with evidenced-based periodization strategies for concurrent strength and endurance training in athletic populations. Both low-intensity exercise endurance (liee) and high-intensity exercise endurance (hiee) have been shown to improve as a result of maximal, high force, low velocity (hflv) and explosive, low-force, high-velocity strength training. Hflv strength training is recommended initially to develop a neuromuscular base for endurance athletes with limited strength training experience. A sequenced approach to strength training involving phases of strength-endurance, basic strength, strength, and power will provide further enhancements in liee and hiee for high-level endurance athletes.

<p>Quality Function Deployment is an extremely useful tool which can be applied within the Systems Engineering Process, to optimize product design and the design process. The use of cross functional teams to analyze customer needs; translate them into design attributes; and subsequently deploy them through every facet of product design, development, and production, can significantly enhance the effectiveness and efficiency of the entire process. Unfortunately the few examples of Quality Function Deployment application, in the academic literature, are generally simplistic and lack any significant depth.</p> <p> The objective of this report is to investigate the application of Quality Function Deployment to a relatively complex product design requirement in an actual manufacturing environment. Specifically, the design and production of engine main bearings at the Federal Mogul plant in Blacksburg, Virginia, are considered.</p> <p> The report examines the use of Quality Function Deployment, as a general design tool; the functional requirements and design constraints of engine main bearings; and the application of one variation of Quality Function Deployment to the evaluation of proposed changes to a bearing's design configuration and the bearing production process.</p> <p> The report concludes with recommendations concerning the implementation of Quality Function Deployment at Federal Mogul, the conduct of Quality Function Deployment instruction at Virginia Tech and a possible avenue for future research.</p> / Master of Science

One of the greatest challenges facing school staff is problem behavior in the classroom (Public Agenda, 2004). Children who engage in problem behavior in the classroom setting greatly challenge teachers and diminish the ability to learn. This study evaluated the effects of self-monitoring using the Individualized Behavior Rating Scale Tool (IBRST) on problem behavior and on-task behavior in a classroom setting using a multiple-baseline across participants design. This study also evaluated the extent to which students self-rating on the IBRST correlated with direct observation data. Results indicate that self-monitoring using the IBRST was an effective strategy for increasing on-task behavior and decreasing problem behavior for all three students. Results also indicate that the IBRST may be an accurate and reliable means of measuring data when direct observation data may not be feasible or possible. There were 56/60 perfect agreements, with the other four opportunities being only 1-pt value apart. Limitations and future research are discussed.